Making Your System Visible: Causal-Loop Diagrams
In making any dynamic system visible using causal-loop diagrams, it is important to understand the role of each of the following structural and functional characteristics of dynamic systems and system modeling.
Balancing Feedback
Balancing feedback will stabilize a system’s behavior. For example a thermostat is a balancing feedback system where the temperature is measured, the difference from the desired temperature measured, and a heating or cooling device adjustment made accordingly. This can be depicted as below, with the B identifying the loop as balancing. When the temperature is higher than the target, then the adjustment is to generate cold air. When the temperature is lower than the target then the adjustment is to generate hot air.
Reinforcing Feedback
Reinforcing feedback will amplify a system’s behavior. For example a bank account is a reinforcing feedback system where you have an account balance, onto which an interest rate is applied, and as a result you have interest paid to increase the balance (assuming your bank pays you interest). This can be depicted as below, with the R identifying the loop as balancing. As the cycle continues, more and more interest is paid, continually increasing your account balance. Conversely, when you have a negative account balance, your bank might apply a charge, which is deducted from your balance (much more likely). This cycle will continue as your account goes into increasing debt.
Delays
What makes systems complex is that there are often delays in the feedback loops. Delays separate cause and effect over time which often leads to instability and oscillation. For example, how many times have you been in the shower and tried to adjust the temperature, only to find the water suddenly get too hot or cold? This is due to a delay in the action of adjusting the temperature, and the temperature actually changing. As a result we tend to over-adjust and get burnt or chilled.
Archetypes
Most systems are not as simple as these examples, and consist of combinations of balancing and reinforcing feedback loops with different delays. However, a system’s particular structure will result in its behavior being constant over time, and systems with similar combinations result in similar behaviors. These patterns which cause similar and recognizable system behavior are known as system archetypes.
Being able to recognize system archetypes helps to identify the cause of behaviors, and gives insight into how to break (or encourage) the archetype to our advantage. Let’s take a look at an example.
Limits to Success
The Limits to Success archetype can be depicted as below.
To improve performance of a system, more efforts are made, which do lead to the anticipated improvements, creating a reinforcing loop. However, after some time the performance reaches a limit and resistance creates a balancing loop, leading to the performance leveling off, declining or even crashing.